5 papers
Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
Project Apertus, Alejandro Hernández-Cano, Alexander Hägele +100
We present Apertus, a fully open suite of large language models (LLMs) designed to address two systemic shortcomings in today's open model ecosystem: data compliance and multilingu…
Contextual Bilevel Reinforcement Learning for Incentive Alignment
Vinzenz Thoma, Barna Pasztor, Andreas Krause +2
The optimal policy in various real-world strategic decision-making problems depends both on the environmental configuration and exogenous events. For these settings, we introduce C…
Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning
Barna Pásztor, Ilija Bogunovic, Andreas Krause
Learning in multi-agent systems is highly challenging due to several factors including the non-stationarity introduced by agents' interactions and the combinatorial nature of their…
On the impact of publicly available news and information transfer to financial markets
Metod Jazbec, Barna Pásztor, Felix Faltings +2
We quantify the propagation and absorption of large-scale publicly available news articles from the World Wide Web to financial markets. To extract publicly available information,…
Stochastic Gradient Descent Works Really Well for Stress Minimization
Katharina Börsig, Ulrik Brandes, Barna Pasztor
Stress minimization is among the best studied force-directed graph layout methods because it reliably yields high-quality layouts. It thus comes as a surprise that a novel approach…